The present invention relates to a feature extracting method, a subject recognizing method and an image processing apparatus all for processing a radiation image, and in particular, to a feature extracting method, a subject recognizing method and an image processing apparatus which are capable of conducting feature extracting necessary for an optimum processing of radiation images.
In recent years, there has been developed an apparatus capable of radiographing a radiation image as a digital image directly. For example, TOKKAISHO Nos. 55-12429 and 63-189853 disclose a method employing a detector that uses a stimulable phosphor, as an apparatus wherein an amount of radiation irradiated on a subject is detected, and a radiation image that is formed depending on an amount of the detection is obtained as an electric signal.
In the aforementioned apparatus, radiation that has passed through a subject once is irradiated on a detector in which a stimulable phosphor is fixed on a sheet-shaped base board in a way of coating or vacuum deposition, so that the radiation may be absorbed in the stimulable phosphor.
After that, the stimulable phosphor is excited with light or heat energy so that radiation energy accumulated in the stimulable phosphor through the absorption stated above may be radiated as fluorescent light which is transferred photoelectrically to obtain an image signal.
On the other hand, there has been proposed an apparatus for detecting a radiation image which is obtained by generating electric charges corresponding to intensity of the radiation irradiated, then, by accumulating the generated electric charges in a plurality of capacitors arranged two-dimensionally, and by taking out the accumulated electric charges.
The radiation image detecting apparatus of this sort employs one called a flat panel detector (FPD). With respect to the FPD of this sort, there is known an object realized by combination of a phosphor that radiates fluorescent light corresponding to intensity of the irradiated radiation and a photoelectric transfer element such as a photodiode or CCD that receives fluorescent light radiated from the phosphor, directly or through a reduction optical system, to conduct photoelectric transfer, as described in TOKKAIHEI No. 9-90048.
As described in TOKKAIHEI No. 6-342098, there is also known the one wherein irradiated radiation is transferred directly into an electric charge.
In these apparatuses mentioned above, it is preferable that an image obtained by the apparatus is automatically transferred in terms of gradation, for the purpose of indicating a radiation image with a gradation that is suited to diagnoses, so that a portion (region of interest) targeted by a medical doctor may become easy to see.
For conducting the automatic gradation transfer of this sort, processing conditions are determined from statistical characteristics of image data (maximum value, minimum value and histogram or the like), such as a lookup table (LUT) wherein output signal values for input signal values are stipulated and gradation transfer processing is conducted for the total image.
Further, for making the structure of details to be easy to see, there are conducted edge enhancement processing and dynamic range compression processing for making both a high density portion and a low density portion to be observed simultaneously easily by narrowing a signal area of the subject.
However, in the case of radiography utilized for a diagnosis, targets to be radiographed include various regions covering from a head to limbs, and the regions to be targeted by medical doctors differ each other for each case. Therefore, the image processing condition for obtaining an image that is optimum for a diagnosis varies depending on a radiographed region. The image processing condition also varies depending on the radiographing direction, in the same way.
In the conventional apparatus in the past, therefore, it is necessary to input a radiographed region on a subject and the orientation.
Some hospitals are equipped with a hospital information system (HIS) or a radiology section information system (RIS), and they can acquire direct radiographed region information from the order information for radiography, and therefore, there is no need for operations of a radiologist, in particular, and optimum processing conditions can be selected. However, in the greater part of hospitals which are not equipped with these systems, radiologists and others need to input information manually.
In the case of urgent radiographing, radiologists or the like sometimes input information of the region of a subject manually, even in the hospitals equipped with the aforesaid HIS or RIS, for quick radiographing.
However, parts of the body radiographed generally include 100 or more types of regions, and it is complicated and troublesome to conduct inputting work for each radiographing, which has been a burden for a radiologist who conducts radiographing.
Therefore, it is demanded to recognize a region and orientation of a subject automatically by reading an image obtained through radiographing, and to select the optimum processing condition, for lightening the burden for the radiologist.
As a method to recognize a part of the body and orientation of a subject, there are methods described in TOKKAI Nos. 2001-76141 and 2001224576. In these methods, a region (subject region) where a subject is radiographed is recognized from the image, then, various feature value are extracted from the region, and a radiographed region and the orientation of the subject are recognized based on the feature value.
To recognize accurately the part of the body radiographed in the method of this sort, it is important to obtain accurately the feature value showing the part of the body of the subject from the image.
On the other hand, in the case of regions which are adjacent to each other, like a lumbar and a coccyx, it sometimes happens that both regions are radiographed on the same image. In this case, if the minute difference is not reflected as a different feature, the feature value obtained are mostly the same, and it is sometimes difficult to distinguish one from another.
Further, on an image of the lumbar, contrast of a subject is relatively low. In the case of the image of this sort, when trying to extract a feature value by investigating signal changes between neighboring pixels, and thereby, by investigating distribution of edge pixels having strong intensity of signal change, it is not possible to obtain the distribution of edge pixels depending on the structure of the subject, and it is sometimes impossible to obtain an effective feature value.
In addition, when trying to investigate presence of a lung field region and thereby to utilize the results of the investigation as feature value, even in the case of an image wherein a lung field is radiographed, a signal difference between the lung field region and the other region is made to be small by the presence of a change to a morbid state in the lung field, thus, recognition of the lung field region is sometimes difficult.
In these cases, if an arrangement is made so that feature value can be extracted based on a minute difference and signal change from the beginning, there is a high possibility that a change of an outline of a local subject region and a slight signal change between neighboring pixels are caught, and feature value which are different from those to be obtained originally are extracted accidentally. When the wrong feature value are extracted, there is a high possibility that the result of recognition of the region to be radiographed of a subject is also wrong.
Therefore, there is a demand for a feature extracting method wherein even a minute difference can be evaluated correctly, and wrong feature value are not extracted.